--- - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: 'Global Annual PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD) data sets represent a series of annual average grids (2001-2010) of fine particulate matter (solid particles and liquid droplets) that were derived from MODIS and MISR AOD satellite data. Together the grids provide a continuous surface of concentrations in micrograms per cubic meter of particulate matter of 2.5 micrometers or smaller (PM2.5) for health and environmental research. The satellite AOD retrievals were converted to ground-level concentrations based on a conversion factor developed by researchers at Dalhousie University that accounts for spatial and temporal variations in aerosol properties and vertical structure as derived from a global 3-D chemical transport model (GEOS-Chem). The raster grids have a grid cell resolution of 30 arc-minutes (0.5 degree or approximately 50 sq. km at the equator) and cover the world from 70°N to 60°S latitude. The grids were produced by researchers at Battelle Memorial Institute in collaboration with the Center for International Earth Science Information Network/Columbia University under a NASA-ROSES project entitled "Using Satellite Data to Develop Environmental Indicators: An Application of NASA Data Products to Support High Level Decisions for National and International Environmental Protection". Exposure to fine particles is associated with premature death as well as increased morbidity from respiratory and cardiovascular disease, especially in the elderly, young children, and those already suffering from these illnesses. The World Health Organization guideline for PM2.5 average annual exposure is less than or equal to 10.0 micrograms per cubic meter, whereas the US Environmental Protection Agency (EPA) primary standard is less than or equal to 12.0 micrograms per cubic meter. The EPA primary standards are designed to protect public health with an adequate margin of safety.' description_attribution: ~ doi: ~ end_time: ~ href: http://52.38.26.42:8080/dataset/nasa-sedac-sdei-global-annual-avg-pm2-5-2001-2010.yaml identifier: nasa-sedac-sdei-global-annual-avg-pm2-5-2001-2010 lat_max: 90.0 lat_min: -55.0 lon_max: 180.0 lon_min: -180.0 name: Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth (AOD) native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: 2001-01-01T00:00:00 temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/nasa-sedac-sdei-global-annual-avg-pm2-5-2001-2010 url: http://reverb.echo.nasa.gov/reverb?selected=C1000000182-SEDAC variables: ~ version: ~ vertical_extent: ~ - access_dt: 2013-08-01T00:00:00 attributes: Annual maximum Great Lakes ice cover cite_metadata: 'Bai, X., and J. Wang, 2012: Atmospheric teleconnection patterns associated with severe and mild ice cover on the Great Lakes, 1963–2011. Water Quality Research Journal of Canada, 47, 421–435, doi:10.2166/wqrjc.2012.009' data_qualifier: ~ description: "Ice cover data is available online for years 2003 through 2013 (partial data for 2012 and 2013). For each year, three types of products are available: original ice charts from the National Ice Center (ASCII files), graphic images of ice maps (jpg files) and ArcGIS feature classes for GIS users (shapefiles). This data is organized by 'ice year' rather than calendar year. For example, ice year 2011 begins with files from December 2010 and ends with May 2011.\r\n\r\nAll of these products were developed according to the standards used for the Great Lakes Ice Atlas for 1973-2002, ensuring that this time series of ice data is internally consistent. Although the ice charts and graphic files for 2003-2005 were released previously (Assel, 2005), they are included here for consistency with the addition of GIS files. For more documentation on this data set, see Wang et al., 2012, and, Assel et al., 2013." description_attribution: ~ doi: ~ end_time: ~ href: http://52.38.26.42:8080/dataset/nca3-amic-r201308.yaml identifier: nca3-amic-r201308 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: Annual Maximum Ice Coverage (AMIC) native_id: N/A processing_level: ~ publication_year: 2012 release_dt: ~ scale: ~ scope: ~ spatial_extent: 'maximum_latitude: 49; minimum_latitude: 41; maximum_longitude: -76; minimum_longitude: -93;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 1963-01-01T00:00:00 2013-07-31T23:59:59 temporal_resolution: ~ type: ~ uri: /dataset/nca3-amic-r201308 url: http://www.glerl.noaa.gov/data/ variables: ~ version: N/A vertical_extent: ~ - access_dt: ~ attributes: 'Monthly average maximum temperature, monthly average minimum temperature, monthly average temperature, total monthly precipitation' cite_metadata: 'Vose, R., S. Applequist, M. Squires, I. Durre, M. Menne, C. Williams, C. Fenimore, K. Gleason, and D. Arndt, 2014: Improved Historical Temperature and Precipitation Time Series For U.S. Climate Divisions. J. Appl. Meteor. Climatol. doi:10.1175/JAMC-D-13-0248.1, in press.' data_qualifier: ~ description: "For many years the Climate Divisional Dataset was the only long-term temporally and spatially complete dataset from which to generate historical climate analyses (1895-2013) for the contiguous United States (CONUS). It was originally developed for climate-division, statewide, regional, national, and population-weighted monitoring of drought, temperature, precipitation, and heating/cooling degree day values. Since the dataset was at the divisional spatial scale, it naturally lent itself to agricultural and hydrological applications.\r\n\r\nThere are 344 climate divisions in the CONUS. For each climate division, monthly station temperature and precipitation values are computed from the daily observations. The divisional values are weighted by area to compute statewide values and the statewide values are weighted by area to compute regional values. (Karl and Koss, 1984)." description_attribution: ~ doi: ~ end_time: ~ href: http://52.38.26.42:8080/dataset/nca3-cddv2-r1.yaml identifier: nca3-cddv2-r1 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: U.S. Climate Divisional Dataset Version 2 native_id: Unknown processing_level: ~ publication_year: 2014 release_dt: 1996-04-29T00:00:00 scale: ~ scope: ~ spatial_extent: 'maximum_latitude: 49; minimum_latitude: 24; maximum_longitude: -65; minimum_longitude: -129;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 1895-01-01T00:00:00 2013-12-31T00:00:00 temporal_resolution: ~ type: ~ uri: /dataset/nca3-cddv2-r1 url: http://www.ncdc.noaa.gov/monitoring-references/maps/us-climate-divisions.php variables: ~ version: 2 vertical_extent: ~ - access_dt: 2013-04-15T00:00:00 attributes: 'Daily precipitation, daily maximum temperature, daily minimum temperature' cite_metadata: 'Hayhoe, K., Stoner, et al., (2013), Development and Dissemination of a High-Resolution National Climate Change Dataset. http://cida.usgs.gov/thredds/fileServer/dcp/files/Hayhoe_USGS_downscaled_database_final_report.pdf' data_qualifier: ~ description: 'In this project, we used an advanced statistical downscaling method that combines high-resolution observations with outputs from 16 different global climate models based on 4 future emission scenarios to generate the most comprehensive dataset of daily temperature and precipitation projections available for climate change impacts in the U.S. The gridded dataset covers the continental United States, southern Canada and northern Mexico at one-eighth degree resolution and Alaska at one-half degree resolution. The high-resolution projections produced by this work have been rigorously quality-controlled for both errors and biases in the global climate and statistical downscaling models. We also calculated projected future changes in a broad range of impact-relevant indicators, from seasonal temperature to extreme precipitation days. The results of the error and bias tests and the indicator calculations are made available as part of this database.' description_attribution: ~ doi: ~ end_time: ~ href: http://52.38.26.42:8080/dataset/nca3-cmip3-downscaled-r201304.yaml identifier: nca3-cmip3-downscaled-r201304 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: Eighth degree-CONUS Daily Downscaled Climate Projections native_id: 0bdee6a2-f677-4714-8d36-0ba570972aba processing_level: ~ publication_year: 2010 release_dt: 2013-12-05T20:42:39 scale: ~ scope: ~ spatial_extent: 'maximum_latitude: 51.68; minimum_latitude: 21.44; maximum_longitude: -65.74; minimum_longitude: -127.97;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 1960-01-01T00:00:00 2099-12-31T23:59:59 temporal_resolution: ~ type: ~ uri: /dataset/nca3-cmip3-downscaled-r201304 url: http://cida.usgs.gov/thredds/catalog.html variables: ~ version: N/A vertical_extent: ~ - access_dt: 2012-05-22T00:00:00 attributes: 'See list at: http://www-pcmdi.llnl.gov/ipcc/standard_output.html' cite_metadata: 'Meehl, G. A., C. Covey, T. Delworth, M. Latif, B. McAvaney, J. F. B. Mitchell, R. J. Stouffer, and K. E. Taylor, 2007: The WCRP CMIP3 multi-model dataset: A new era in climate change research, Bulletin of the American Meteorological Society, 88, 1383-1394. DOI: 10.1175/BAMS-88-9-1383' data_qualifier: ~ description: "Under the World Climate Research Programme (WCRP), the Working Group on Cloupled Modelling (WGCM) established the Coupled Model Intercomparison Project (CMIP) as a standard experimental protocol for studying the output of coupled atmosphere-ocean general circulation models (AOGCMs). CMIP provides a community-based infrastructure in support of climate model diagnosis, validation, intercomparison, documentation and data access. This framework enables a diverse community of scientists to analyze GCMs in a systematic fashion, a process which serves to facilitate model improvement.\r\n\r\nThe Program for Climate Model Diagnosis and Intercomparison (PCMDI) archives much of the CMIP data. Part of the CMIP archive constitutes phase 3 of the Coupled Model Intercomparison Project (CMIP3), a collection of climate model output from simulations of the past, present and future climate.\r\n\r\nThis unprecedented collection of recent model output is officially known as the \"WCRP CMIP3 multi-model dataset\". It is meant to serve the Intergovernmental Panel on Climate Change (IPCC)'s Working Group 1, which focuses on the physical climate system -- atmosphere, land surface, ocean and sea ice -- and the choice of variables archived reflects this focus. The Intergovernmental Panel on Climate Change (IPCC) was established by the World Meteorological Organization and the United Nations Environmental Program to assess scientific information on climate change. The IPCC publishes reports that summarize the state of the science.\r\n\r\nThe research based on this dataset provided much of the new material underlying the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4)." description_attribution: ~ doi: ~ end_time: ~ href: http://52.38.26.42:8080/dataset/nca3-cmip3-r201205.yaml identifier: nca3-cmip3-r201205 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset native_id: Unknown processing_level: ~ publication_year: 2010 release_dt: ~ scale: ~ scope: ~ spatial_extent: 'maximum_latitude: 90; minimum_latitude: -90; maximum_longitude: 180; minimum_longitude: -180;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 1850-01-01T00:00:00 2300-12-31T23:59:59 temporal_resolution: ~ type: ~ uri: /dataset/nca3-cmip3-r201205 url: http://www-pcmdi.llnl.gov/ipcc/about_ipcc.php variables: ~ version: N/A vertical_extent: ~ - access_dt: ~ attributes: 'See list at: http://cmip-pcmdi.llnl.gov/cmip5/docs/standard_output.pdf' cite_metadata: 'Taylor, K.E., R.J. Stouffer, G.A. Meehl: An Overview of CMIP5 and the experiment design.” Bull. Amer. Meteor. Soc., 93, 485-498, doi:10.1175/BAMS-D-11-00094.1, 2012.' data_qualifier: ~ description: "At a September 2008 meeting involving 20 climate modeling groups from around the world, the WCRP's Working Group on Coupled Modelling (WGCM), with input from the IGBP AIMES project, agreed to promote a new set of coordinated climate model experiments. These experiments comprise the fifth phase of the Coupled Model Intercomparison Project (CMIP5). CMIP5 will notably provide a multi-model context for 1) assessing the mechanisms responsible for model differences in poorly understood feedbacks associated with the carbon cycle and with clouds, 2) examining climate “predictability” and exploring the ability of models to predict climate on decadal time scales, and, more generally, 3) determining why similarly forced models produce a range of responses.\r\n\r\nCMIP5 promotes a standard set of model simulations in order to:\r\n* evaluate how realistic the models are in simulating the recent past,\r\n* provide projections of future climate change on two time scales, near term (out to about 2035) and long term (out to 2100 and beyond), and\r\n* understand some of the factors responsible for differences in model projections, including quantifying some key feedbacks such as those involving clouds and the carbon cycle." description_attribution: ~ doi: ~ end_time: ~ href: http://52.38.26.42:8080/dataset/nca3-cmip5-r1.yaml identifier: nca3-cmip5-r1 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: World Climate Research Program's (WCRP's) Coupled Model Intercomparison Project phase 5 (CMIP5) multi-model ensemble native_id: Unknown processing_level: ~ publication_year: 2012 release_dt: ~ scale: ~ scope: ~ spatial_extent: 'maximum_latitude: 90.00; minimum_latitude: -90.00; maximum_longitude: 180.00; minimum_longitude: -180.00;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 1850-01-01T00:00:00 2300-12-31T23:59:59 temporal_resolution: ~ type: ~ uri: /dataset/nca3-cmip5-r1 url: http://cmip-pcmdi.llnl.gov/cmip5/data_portal.html variables: ~ version: N/A vertical_extent: ~ - access_dt: ~ attributes: 'C02 Emissions: metric tons of carbon (gas, liquids, solids, cement production, gas flaring, and per Capita)' cite_metadata: 'Boden, T., G. Marland, and R. Andres, 2012: Global, regional, and national fossil-fuel CO2 emissions. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, US Department of Energy, Oak Ridge, Tenn., USA' data_qualifier: ~ description: "Since 1751 approximately 356 billion metric tonnes of carbon have been released to the atmosphere from the consumption of fossil fuels and cement production. Half of these fossil-fuel CO2 emissions have occurred since the mid 1980s. The 2009 global fossil-fuel carbon emission estimate, 8738 million metric tons of carbon, represents a slight decline of 0.35% from an all-time high (8769 million metric tons of carbon) in 2008. The slight decline is due to the Global Financial Crisis which began in mid-2008 and had obvious economic and energy use consequences, particularly in North America and Europe.\r\n\r\nGlobally, liquid and solid fuels accounted for 76.6% of the emissions from fossil-fuel burning and cement production in 2009. Combustion of gas fuels (e.g., natural gas) accounted for 17.9% (1568 million metric tons of carbon) of the total emissions from fossil fuels in 2009 and reflects a gradually increasing global utilization of natural gas. Emissions from cement production (413 million metric tons of carbon in 2009) have more than doubled since the mid 1990s and now represent 4.7% of global CO2 releases from fossil-fuel burning and cement production. Gas flaring, which accounted for roughly 2% of global emissions during the 1970s, now accounts for less than 1% of global fossil-fuel releases." description_attribution: ~ doi: ~ end_time: ~ href: http://52.38.26.42:8080/dataset/nca3-doe-co2-r201209.yaml identifier: nca3-doe-co2-r201209 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'Global CO2 Emissions from Fossil-Fuel Burning, Cement Manufacture, and Gas Flaring: 1751-2009' native_id: 'DOI: 10.3334/CDIAC/00001_V2012' processing_level: ~ publication_year: 2012 release_dt: 2012-09-20T00:00:00 scale: ~ scope: ~ spatial_extent: 'maximum_latitude: 90.00; minimum_latitude: -90.00; maximum_longitude: 180.00; minimum_longitude: -180.00;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 1751-01-01T00:00:00 2009-12-31T23:59:59 temporal_resolution: ~ type: ~ uri: /dataset/nca3-doe-co2-r201209 url: http://cdiac.ornl.gov/ftp/ndp030/global.1751_2009.ems variables: ~ version: N/A vertical_extent: ~ - access_dt: 2013-07-31T00:00:00 attributes: Carbon Dioxide Concentration (ppmv) cite_metadata: 'Earth Policy Institute: Data Center - Climate, Energy, and Transportation (http://www.earth-policy.org/data_center/C23)' data_qualifier: ~ description: "Atmospheric carbon dioxide concentration for the years 1000-2012.\t\t\t\t\t\r\n\r\nSource: Compiled by Earth Policy Institute, with long term historical data from Worldwatch Institute, based on Thomas A. Boden et al., Trends '93: A Compendium of Data on Global Change (Oak Ridge, TN: Oak Ridge National Laboratory, September 1994), and J.T. Houghton et al., eds., Climate Change 1995: The Science of Climate Change, Contribution of Working Group I to the Second Assessment Report of the Intergovernmental Panel on Climate Change (New York: Cambridge University Press, 1996); 1959 to 2012 from National Oceanic and Atmospheric Administration Earth System Research Laboratory, \"Mauna Loa CO2 Annual Mean Data,\" at www.esrl.noaa.gov/gmd/ccgg/trends/co2_data_mlo.html, updated 5 June 2013." description_attribution: ~ doi: ~ end_time: ~ href: http://52.38.26.42:8080/dataset/nca3-epi-co2-r201307.yaml identifier: nca3-epi-co2-r201307 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'Earth Policy Institute Atmospheric Carbon Dioxide Concentration, 1000-2012' native_id: Unknown processing_level: ~ publication_year: 2013 release_dt: ~ scale: ~ scope: ~ spatial_extent: 'maximum_latitude: 90.00; minimum_latitude: -90.00; maximum_longitude: 180.00; minimum_longitude: -180.00;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 1000-01-01T00:00:00 2012-12-31T23:59:59 temporal_resolution: ~ type: ~ uri: /dataset/nca3-epi-co2-r201307 url: http://www.earth-policy.org/data_center/C23/ variables: ~ version: Unknown vertical_extent: ~ - access_dt: ~ attributes: Atmospheric Carbon Dioxide concentrations cite_metadata: "Lüthi, D., M. Le Floch, B. Bereiter, T. Blunier, J.-M. Barnola, \r\nU. Siegenthaler, D. Raynaud, J. Jouzel, H. Fischer, K. Kawamura, \r\nand T.F. Stocker. 2008.\r\nHigh-resolution carbon dioxide concentration record 650,000-800,000 \r\nyears before present. Nature, Vol. 453, pp. 379-382, 15 May 2008. doi:10.1038/nature06949" data_qualifier: ~ description: "Changes in past atmospheric carbon dioxide concentrations can be determined by measuring the composition of air trapped in ice cores from Antarctica. So far, the Antarctic Vostok and EPICA Dome C ice cores have provided a composite record of atmospheric carbon dioxide levels over the past 650,000 years. Here we present results of the lowest 200m of the Dome C ice core, extending the record of atmospheric carbon dioxide concentration by two complete glacial cycles to 800,000 yr before present. From previously published data and the present work, we find that atmospheric carbon dioxide is strongly correlated with Antarctic temperature throughout eight glacial cycles but with significantly lower concentrations between 650,000 and 750,000 yr before present.\r\n\r\nCarbon dioxide levels are below 180 parts per million by volume (p.p.m.v.) for a period of 3,000 yr during Marine Isotope Stage 16, possibly reflecting more pronounced oceanic carbon storage. We report the lowest carbon dioxide concentration measured in an ice core, which extends the pre-industrial range of carbon dioxide concentrations during the late Quaternary by about 10 p.p.m.v. to 172–300 p.p.m.v" description_attribution: ~ doi: 10.1038/nature06949 end_time: ~ href: http://52.38.26.42:8080/dataset/nca3-epica-ice-core-r20080515.yaml identifier: nca3-epica-ice-core-r20080515 lat_max: 90 lat_min: -90 lon_max: 180 lon_min: -180 name: EPICA Dome C Ice Core 800KYr Carbon Dioxide Data native_id: DOI:10.1038/nature06949 processing_level: ~ publication_year: 2008 release_dt: 2008-05-15T00:00:00 scale: ~ scope: ~ spatial_extent: 'maximum_latitude: 90.00; minimum_latitude: -90.00; maximum_longitude: 180.00; minimum_longitude: -180.00;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/nca3-epica-ice-core-r20080515 url: ftp://ftp.ncdc.noaa.gov/pub/data/paleo/icecore/antarctica/epica_domec/edc-co2-2008.txt variables: ~ version: N/A vertical_extent: ~ - access_dt: 2013-05-06T00:00:00 attributes: 'Monthly maximum 1-day precipitation, Maximum number of consecutive days with RR < 1mm, and other temperature and precipitation indices (see http://etccdi.pacificclimate.org/list_27_indices.shtml).' cite_metadata: "Sillmann, J., V. V. Kharin, F. W. Zwiers, X. Zhang, and D. Bronaugh, 2013a: Climate extremes indices in the CMIP5 multi-model ensemble. Part 1: Model evaluation in the present climate. J. Geophys. Res., doi:10.1002/jgrd.50203.\r\n\r\nSillmann, J., V. V. Kharin, F. W. Zwiers, X. Zhang, and D. Bronaugh, 2013b: Climate extremes indices in the CMIP5 multi-model ensemble. Part 2: Future projections. J. Geophys. Res., doi:10.1002/jgrd.50188." data_qualifier: ~ description: 'The climate extremes indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) are computed for a number of global climate models participating in the Coupled Model Intercomparison Project Phase 3 (CMIP3) and Phase 5 (CMIP5), and reanalyses. The definitions of the indices are given here. The validation of climate extremes indices and analysis of their projected future changes simulated by the CMIP5 models is presented in Sillmann et al. (2013a, 2013b)' description_attribution: ~ doi: ~ end_time: ~ href: http://52.38.26.42:8080/dataset/nca3-etccdi-r201305.yaml identifier: nca3-etccdi-r201305 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: ETCCDI Extremes Indices Archive native_id: Unknown processing_level: ~ publication_year: 2013 release_dt: 2012-09-12T00:00:00 scale: ~ scope: ~ spatial_extent: 'maximum_latitude: 90; minimum_latitude: -90; maximum_longitude: 180; minimum_longitude: -180;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 1850-01-01T00:00:00 2300-12-31T23:59:59 temporal_resolution: ~ type: ~ uri: /dataset/nca3-etccdi-r201305 url: http://www.cccma.ec.gc.ca/data/climdex/climdex.shtml variables: ~ version: N/A vertical_extent: ~ - access_dt: 2013-05-01T00:00:00 attributes: 'Daily maximum, daily minimum temperature, daily precipitation, snowfall, snow depth' cite_metadata: 'Menne, Matthew J., Imke Durre, Russell S. Vose, Byron E. Gleason, Tamara G. Houston, 2012: An Overview of the Global Historical Climatology Network-Daily Database. J. Atmos. Oceanic Technol., 29, 897–910, doi:10.1175/JTECH-D-11-00103.1.' data_qualifier: ~ description: "GHCN (Global Historical Climatology Network)-Daily is an integrated database of daily climate summaries from land surface stations across the globe. Like its monthly counterpart (GHCN-Monthly), GHCN-Daily is comprised of daily climate records from numerous sources that have been integrated and subjected to a common suite of quality assurance reviews.\r\n\r\nGHCN-Daily contains records from over 75000 stations in 180 countries and territories. Numerous daily variables are provided, including maximum and minimum temperature, total daily precipitation, snowfall, and snow depth; however, about two thirds of the stations report precipitation only. Both the record length and period of record vary by station and cover intervals ranging from less than year to more than 175 years." description_attribution: ~ doi: ~ end_time: ~ href: http://52.38.26.42:8080/dataset/nca3-ghcn-daily-r201305.yaml identifier: nca3-ghcn-daily-r201305 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'Global Historical Climatology Network - Daily' native_id: 9101 processing_level: ~ publication_year: 2012 release_dt: 2006-04-29T00:00:00 scale: ~ scope: ~ spatial_extent: 'maximum_latitude: -90.00; minimum_latitude: 90.00; maximum_longitude: -180.00; minimum_longitude: 180.00;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 1767-01-01T00:00:00 2013-04-30T00:00:00 temporal_resolution: ~ type: ~ uri: /dataset/nca3-ghcn-daily-r201305 url: http://www.ncdc.noaa.gov/oa/climate/ghcn-daily/index.php?name=data variables: ~ version: Version 3.02-upd-2013050105 vertical_extent: ~ - access_dt: 2013-05-13T00:00:00 attributes: 'Monthly mean maximum temperature, monthly mean minimum temperature, monthly mean temperature, and total monthly precipitation' cite_metadata: "Temperature: Lawrimore, J. H., M. J. Menne, B. E. Gleason, C. N. Williams, D.\r\nB. Wuertz, R. S. Vose, and J. Rennie (2011), An overview of the Global Historical Climatology Network monthly mean temperature data set, version 3, J. Geophys. Res., 116, D19121, doi:10.1029/2011JD016187.\r\n\r\nPrecipitation: Vose, R. S., R. L. Schmoyer, P. M. Steurer, T. C. Peterson, R. Heim, T. R. Karl, and J. Eischeid, 1992: The Global Historical Climatology Network: Long-term monthly temperature, precipitation, sea level pressure, and station pressure data. ORNL/CDIAC-53, NDP-041, 325 pp. [Available from Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831.]" data_qualifier: ~ description: "The GHCN-monthly data set provides monthly mean in situ surface air temperature and precipitation data. Data is available for some locations dating back to the 1700s. There is global coverage from 1880 to the present. The data is updated each month with the most recent month's data. Quality controlled and homogeneity adjusted data sets are available. There are 7,280 mean temperature stations and more than 20,000 precipitation stations." description_attribution: ~ doi: ~ end_time: ~ href: http://52.38.26.42:8080/dataset/nca3-ghcn-monthly-r201305.yaml identifier: nca3-ghcn-monthly-r201305 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'Global Historical Climatology Network - Monthly' native_id: N/A processing_level: ~ publication_year: 1997 release_dt: ~ scale: ~ scope: ~ spatial_extent: 'maximum_latitude: 90.00; minimum_latitude: -90.00; maximum_longitude: 180.00; minimum_longitude: -180.00;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 1880-01-31T00:00:00 2013-08-31T00:00:00 temporal_resolution: ~ type: ~ uri: /dataset/nca3-ghcn-monthly-r201305 url: https://www.ncdc.noaa.gov/ghcnm/ variables: ~ version: 'Version 2 (temperature), Version 3 (precipitation)' vertical_extent: ~ - access_dt: 2014-01-21T00:00:00 attributes: Maximum and minimum temperature; precipitation cite_metadata: 'Menne, Matthew J., Imke Durre, Russell S. Vose, Byron E. Gleason, Tamara G. Houston, 2012: An Overview of the Global Historical Climatology Network-Daily Database. J. Atmos. Oceanic Technol., 29, 897–910, doi:10.1175/JTECH-D-11-00103.1.' data_qualifier: ~ description: "These data are the North American subset of the Global Historical Climatology Network-Daily (GHCN-D) Monthly Summaries that have been homogenized in the USHCNv2.5 portion of the GHCN-M v3.2.2 operational system.\r\n\r\nGHCN-Daily Monthly Summaries is a product derived from GHCN-Daily. Values are simple averages or monthly accumulations. GHCN-Daily is a data set whose aim is to address the need for historical daily records over global land areas. Like its monthly counterpart, GHCN-Monthly, GHCN-Daily is a composite of climate records from numerous sources that were merged and then subjected to a suite of quality assurance reviews. The meteorological elements measured for the data set include maximum and minimum temperature, and precipitation." description_attribution: ~ doi: ~ end_time: ~ href: http://52.38.26.42:8080/dataset/nca3-ghcnd-monthly-summaries-r201401.yaml identifier: nca3-ghcnd-monthly-summaries-r201401 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'Global Historical Climatology Network-Daily (GHCN-D) Monthly Summaries: North American subset' native_id: Unknown processing_level: ~ publication_year: 2012 release_dt: 2006-12-21T00:00:00 scale: ~ scope: ~ spatial_extent: 'maximum_latitude: 83; minimum_latitude: 15; maximum_longitude: 173; minimum_longitude: -53;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 1880-01-01T00:00:00 2013-12-31T23:59:59 temporal_resolution: ~ type: ~ uri: /dataset/nca3-ghcnd-monthly-summaries-r201401 url: http://www.ncdc.noaa.gov/cdo-web/search?datasetid=GHCNDMS variables: ~ version: GHCN-M v3.2.2 vertical_extent: ~ - access_dt: ~ attributes: "Combined Land-Surface Air and Sea-Surface Water Temperature Anomalies (Land-Ocean Temperature Index, LOTI):\r\n-Global-mean monthly, seasonal, and annual means, 1880-present, updated through most recent month\r\n-Northern Hemisphere-mean monthly, seasonal, and annual means, 1880-present, updated through most recent month\r\n-Southern Hemisphere-mean monthly, seasonal, and annual means, 1880-present, updated through most recent month\r\n-Zonal annual means, 1880-present, updated through most recent completed year\r\n\r\nMeans Based on Land-Surface Air Temperature Anomalies Only (Meteorological Station Data, dTs):\r\n-Global-mean monthly, seasonal, and annual means, 1880-present, updated through most recent month\r\n-Northern Hemisphere-mean monthly, seasonal, and annual means, 1880-present, updated through most recent month\r\n-Southern Hemisphere-mean monthly, seasonal, and annual means, 1880-present, updated through most recent month\r\n-Zonal annual means, 1880-present, updated through most recent complete calendar year" cite_metadata: 'Hansen, J., R. Ruedy, M. Sato, and K. Lo, 2010: Global surface temperature change, Rev. Geophys., 48, RG4004, doi:10.1029/2010RG000345' data_qualifier: ~ description: "The NASA GISS Surface Temperature Analysis (GISTEMP) provides a measure of the changing global surface temperature with monthly resolution for the period since 1880, when a reasonably global distribution of meteorological stations was established. Input data for the analysis, collected by many national meteorological services around the world, is the unadjusted data of the Global Historical Climatology Network (Peterson and Vose, 1997) except that the USHCN station records included were replaced by a later corrected version. These data were augmented by SCAR data from Antarctic stations. Documentation of our analysis is provided by Hansen et al. (1999), with several modifications described by Hansen et al. (2001). The GISS analysis is updated monthly.\r\n \r\nThe data is available on an equal area grid. NASA provides code to read it onto a 2x2 grid. They have two smoothing levels available for their updated data: 250km and 1200km smoothing. They make available a land only version and a version which includes the hadISST (post Dec 1981) and NOAA OI V2 for data over the oceans. There ARE missing data values." description_attribution: ~ doi: ~ end_time: ~ href: http://52.38.26.42:8080/dataset/nca3-gistemp-r2010.yaml identifier: nca3-gistemp-r2010 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: GISS Surface Temperature Analysis (GISTEMP) native_id: Unknown processing_level: ~ publication_year: 2010 release_dt: 1981-10-29T00:00:00 scale: ~ scope: ~ spatial_extent: 'maximum_latitude: 90.00; minimum_latitude: -90.00; maximum_longitude: 180.00; minimum_longitude: -180.00;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 1880-01-01T00:00:00 2012-12-31T23:59:59 temporal_resolution: ~ type: ~ uri: /dataset/nca3-gistemp-r2010 url: http://data.giss.nasa.gov/gistemp/ variables: ~ version: N/A vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: ~ description_attribution: ~ doi: 10.3334/CDIAC/00001_V2011 end_time: ~ href: http://52.38.26.42:8080/dataset/nca3-global-1751-2008.yaml identifier: nca3-global-1751-2008 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: ~ native_id: ~ processing_level: ~ publication_year: 2011 release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/nca3-global-1751-2008 url: http://cdiac.ornl.gov/ftp/ndp030/global.1751_2008.ems variables: ~ version: ~ vertical_extent: ~ - access_dt: 2012-11-18T00:00:00 attributes: 'Population count for the years 1990, 1995, and 2000' cite_metadata: 'Center for International Earth Science Information Network (CIESIN), Columbia University; and Centro Internacional de Agricultura Tropical (CIAT). 2005. Gridded Population of the World Version 3 (GPWv3): Population Count Grid. Palisades, NY: Socioeconomic Data and Applications Center (SEDAC), Columbia University. Available at http://sedac.ciesin.columbia.edu/gpw.' data_qualifier: ~ description: 'Gridded Population of the World, Version 3 (GPWv3) consists of estimates of human population for the years 1990, 1995, and 2000 by 2.5 arc-minute grid cells and associated data sets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative units, is used to assign population values to grid cells. The population count grids contain estimates of the number of persons per grid cell. The grids are available in various GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).' description_attribution: ~ doi: ~ end_time: ~ href: http://52.38.26.42:8080/dataset/nca3-gpwv3-r201211.yaml identifier: nca3-gpwv3-r201211 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: 'Gridded Population of the World Version 3 (GPWv3): Population Count Grid' native_id: Unknown processing_level: ~ publication_year: 2005 release_dt: ~ scale: ~ scope: ~ spatial_extent: 'maximum_latitude: 85; minimum_latitude: -58; maximum_longitude: 180; minimum_longitude: -180;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 1990-01-01T00:00:00 2000-12-31T00:00:00 temporal_resolution: ~ type: ~ uri: /dataset/nca3-gpwv3-r201211 url: http://sedac.ciesin.columbia.edu/data/set/gpw-v3-population-count variables: ~ version: 3.00 vertical_extent: ~ - access_dt: 2013-07-10T00:00:00 attributes: Time-variable gravity cite_metadata: 'Bettadpur, S. 2007. Gravity Recovery and Climate Experiment Level-2 Gravity Field Product User Handbook. Center for Space Research at The University of Texas at Austin ftp://podaac.jpl.nasa.gov/allData/grace/docs/L2-UserHandbook_v2.3.pdf' data_qualifier: ~ description: 'This dataset contains estimates of Earths static field geototential derived from the Gravity Recovery and Climate Experiment (GRACE) mission measurements, produced by the Jet Propulsion Laboratory (JPL). The data are in spherical harmonics averaged over approximately a month. The primary objective of the GRACE mission is to obtain accurate estimates of the mean and time-variable components of the Earths gravity field variations. This objective is achieved by making continuous measurements of the change in distance between twin spacecraft, co-orbiting in about 500 km altitude, near circular, polar orbit, spaced approximately 200 km apart, using a microwave ranging system. In addition to these range change, the non-gravitional forces are measured on each satellite using a high accuracy electrostatic, room-temperature accelerometer. The satellite orientation and position (and timing) are precisely measured using twin star cameras and a GPS receiver, respectively. Spatial and temporal variations in the Earths gravity field affect the orbits (or trajectories) of the twin spacecraft differently. These differences are manifested as changes in the distance between the spacecraft, as they orbit the Earth. This change in distance is reflected in the time-of-flight of microwave signals transmitted and received nearly simultaneously between the two spacecraft. The change in this time of fight is continuously measured by tracking the phase of the microwave carrier signals. The so called dual-one-way range change measurements can be reconstructed from these phase measurements. This range change (or its numerically derived derivatives), along with other mission and ancillary data, is subsequently analyzed to extract the parameters of an Earth gravity field model.' description_attribution: ~ doi: ~ end_time: ~ href: http://52.38.26.42:8080/dataset/nca3-grace-r201307.yaml identifier: nca3-grace-r201307 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: GRACE Static Field Geopotential Coefficients JPL Release 5.0 GSM native_id: TBD processing_level: ~ publication_year: 2012 release_dt: 2012-03-15T00:00:00 scale: ~ scope: ~ spatial_extent: 'maximum_latitude: -90.00; minimum_latitude: 90.00; maximum_longitude: -180.00; minimum_longitude: 180.00;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 2003-01-01T00:00:00 2012-12-31T23:59:59 temporal_resolution: ~ type: ~ uri: /dataset/nca3-grace-r201307 url: http://podaac.jpl.nasa.gov/dataset/GRACE_GSM_L2_GRAV_JPL_RL05?ids=Platform:ProcessingLevel:TemporalResolution&values=GRACE:*2*:1 variables: ~ version: Release 05 vertical_extent: ~ - access_dt: ~ attributes: Global historical surface temperature anomalies relative to a 1961-1990 reference period. cite_metadata: 'Morice, C.P., J.J. Kennedy, N.A. Rayner, and P.D. Jones, 2012: Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 data set. J. Geophys. Res., 117, D08101, doi: 10.1029/2011JD017187.' data_qualifier: ~ description: "HadCRUT4 is a gridded dataset of global historical surface temperature anomalies relative to a 1961-1990 reference period. Data are available for each month since January 1850, on a 5 degree grid. The dataset is a collaborative product of the Met Office Hadley Centre and the Climatic Research Unit at the University of East Anglia.\r\n\r\nThe gridded data are a blend of the CRUTEM4 land-surface air temperature dataset and the HadSST3 sea-surface temperature (SST) dataset. The dataset is presented as an ensemble of 100 dataset realisations that sample the distribution of uncertainty in the global temperature record given current understanding of non-climatic factors affecting near-surface temperature observations. This ensemble approach allows characterisation of spatially and temporally correlated uncertainty structure in the gridded data, for example arising from uncertainties in methods used to account for changes in SST measurement practices, homogenisation of land station records and the potential impacts of urbanisation.\r\n\r\nThe HadCRUT4 data are neither interpolated nor variance adjusted." description_attribution: ~ doi: ~ end_time: ~ href: http://52.38.26.42:8080/dataset/nca3-hadcrut4-v4_1_1_0.yaml identifier: nca3-hadcrut4-v4_1_1_0 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: HadCRUT4 native_id: Unknown processing_level: ~ publication_year: 2012 release_dt: 2012-10-29T00:00:00 scale: ~ scope: ~ spatial_extent: 'maximum_latitude: 90.00; minimum_latitude: -90.00; maximum_longitude: 180.00; minimum_longitude: -180.00;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 1850-01-01T00:00:00 2012-12-31T23:59:59 temporal_resolution: ~ type: ~ uri: /dataset/nca3-hadcrut4-v4_1_1_0 url: http://www.metoffice.gov.uk/hadobs/hadcrut4/data/current/download.html variables: ~ version: 4.1.1.0 vertical_extent: ~ - access_dt: ~ attributes: ~ cite_metadata: ~ data_qualifier: ~ description: ~ description_attribution: ~ doi: ~ end_time: ~ href: http://52.38.26.42:8080/dataset/nca3-heating-cooling-degree-day-data-r1.yaml identifier: nca3-heating-cooling-degree-day-data-r1 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: Heating & Cooling Degree Day Data native_id: ~ processing_level: ~ publication_year: ~ release_dt: ~ scale: ~ scope: ~ spatial_extent: ~ spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: ~ temporal_resolution: ~ type: ~ uri: /dataset/nca3-heating-cooling-degree-day-data-r1 url: http://www.ncdc.noaa.gov/oa/documentlibrary/hcs/hcs.html variables: ~ version: ~ vertical_extent: ~ - access_dt: ~ attributes: 'storm position, storm intensity' cite_metadata: 'Kossin, J. P., K. R. Knapp, D. J. Vimont, R. J. Murnane, and B. A. Harper, 2007: A globally consistent reanalysis of hurricane variability and trends. Geophys. Res. Lett., 34, L04815, DOI:10.1029/2006GL028836' data_qualifier: ~ description: 'Kossin, J. P., K. R. Knapp, D. J. Vimont, R. J. Murnane, and B. A. Harper, 2007: A globally consistent reanalysis of hurricane variability and trends. Geophys. Res. Lett., 34, L04815, DOI:10.1029/2006GL028836' description_attribution: ~ doi: ~ end_time: ~ href: http://52.38.26.42:8080/dataset/nca3-hursat-r1.yaml identifier: nca3-hursat-r1 lat_max: ~ lat_min: ~ lon_max: ~ lon_min: ~ name: UW/NCDC Satellite Derived Hurricane Intensity Dataset native_id: ~ processing_level: ~ publication_year: 2007 release_dt: 2007-02-28T00:00:00 scale: ~ scope: ~ spatial_extent: 'maximum_latitude: 90.00; minimum_latitude: -90.00; maximum_longitude: 180.00; minimum_longitude: -180.00;' spatial_ref_sys: ~ spatial_res: ~ start_time: ~ temporal_extent: 1979-01-01T00:00:00 2007-12-31T23:59:59 temporal_resolution: ~ type: ~ uri: /dataset/nca3-hursat-r1 url: http://www.ncdc.noaa.gov/hursat/ variables: ~ version: N/A vertical_extent: ~